دورية أكاديمية

A data-driven Boolean model explains memory subsets and evolution in CD8+ T cell exhaustion.

التفاصيل البيبلوغرافية
العنوان: A data-driven Boolean model explains memory subsets and evolution in CD8+ T cell exhaustion.
المؤلفون: Ildefonso GV; Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA., Finley SD; Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA. sfinley@usc.edu.; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA. sfinley@usc.edu.; Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California, USA. sfinley@usc.edu.
المصدر: NPJ systems biology and applications [NPJ Syst Biol Appl] 2023 Jul 31; Vol. 9 (1), pp. 36. Date of Electronic Publication: 2023 Jul 31.
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Nature Publishing Group in partnership with SBI, The Systems Biology Institute Country of Publication: England NLM ID: 101677786 Publication Model: Electronic Cited Medium: Internet ISSN: 2056-7189 (Electronic) Linking ISSN: 20567189 NLM ISO Abbreviation: NPJ Syst Biol Appl Subsets: MEDLINE
أسماء مطبوعة: Original Publication: [London] : Nature Publishing Group in partnership with SBI, The Systems Biology Institute, [2015]-
مواضيع طبية MeSH: T-Cell Exhaustion* , Neoplasms*/genetics , Neoplasms*/metabolism, Humans ; CD8-Positive T-Lymphocytes/metabolism ; Cell Differentiation/genetics ; Lymphocyte Activation
مستخلص: T cells play a key role in a variety of immune responses, including infection and cancer. Upon stimulation, naïve CD8+ T cells proliferate and differentiate into a variety of memory and effector cell types; however, failure to clear antigens causes prolonged stimulation of CD8+ T cells, ultimately leading to T cell exhaustion (TCE). The functional and phenotypic changes that occur during CD8+ T cell differentiation are well characterized, but the underlying gene expression state changes are not completely understood. Here, we utilize a previously published data-driven Boolean model of gene regulatory interactions shown to mediate TCE. Our network analysis and modeling reveal the final gene expression states that correspond to TCE, along with the sequence of gene expression patterns that give rise to those final states. With a model that predicts the changes in gene expression that lead to TCE, we could evaluate strategies to inhibit the exhausted state. Overall, we demonstrate that a common pathway model of CD8+ T cell gene regulatory interactions can provide insights into the transcriptional changes underlying the evolution of cell states in TCE.
(© 2023. The Author(s).)
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تواريخ الأحداث: Date Created: 20230731 Date Completed: 20230802 Latest Revision: 20230803
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC10390540
DOI: 10.1038/s41540-023-00297-2
PMID: 37524735
قاعدة البيانات: MEDLINE
الوصف
تدمد:2056-7189
DOI:10.1038/s41540-023-00297-2